All right.
By manipulating the variables—like rainfall, warmer weather, melting snowpack—faster than expected, emergency planners can visualize a range of scenarios and optimize their planning. This could include prepositioning breakwaters and sandbags, doing rehearsals and preparation, or starting mobilization of volunteer networks in anticipation of the flooding.
Manipulating variables and risk models does not guarantee perfect forecasting of the magnitude of the risk. Nothing does. However, it does allow for a range of plausible outcomes to be presented to planners and decision-makers before a crisis, based on the best science we have available.
There is a cost to developing and working with the models. Data models need to be built and constantly revalidated. Data from mobile sources needs to be collected. Visual analytic products need to be developed. Decision-makers and planners need to be briefed on the range of possible outcomes. However, much of this data is already available for these models, collected by federal, provincial or municipal agencies. It is a question of integration to facilitate robust risk assessments and forecasts. The cost of integrating the risk models will inevitably be lower than the cost of response and recovery.
As we know from Dunrobin, just west of Ottawa, the cleanup of the flood of 2019 will also include cleanup of the last of the 2018 tornado debris. Fort McMurray is forever changed by the wildfire of 2016. Homes destroyed by fires and floods will have displaced entire communities and changed their attitudes and fabric forever. The question surrounding the social damage and social costs cannot be ignored, and neither can they be measured in the same way as money. This must be considered when developing risk assessment tools to improve our collective capacity for emergency management and public risk communication. Houses can be rebuilt. Communities can never be rebuilt the same way.
In conclusion, using integrated science-based predictive risk models and visual GIS-based maps will permit decision-makers and planners to better appreciate the potential risk to communities and individuals situated within their shared watershed. When these results are communicated to the public, they will provide a better appreciation of the complexity and magnitude of these collective risks. The maps and models needed to accomplish this for the most part already exist and need to be used more effectively, especially for public communication. The costs of doing so are marginal compared to the benefits this will provide in our capacity to forecast and plan for disasters.
Based on extreme weather trends that have been observed in the past few years and decades, it is crucial that we adopt a proactive and predictive approach to planning and preparedness and move away from the reactive approach that has been taken in the past.